The analysis of three level inverter circuit with regard to current harmonic distortion by using ANFIS (original) (raw)
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2012 IEEE 5th India International Conference on Power Electronics (IICPE), 2012
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Enhance the accuracy of control algorithm for multilevel inverter based on artificial neural network
Indonesian Journal of Electrical Engineering and Computer Science
In converters or multilevel inverters it is very important to ensure that the output of themultilevel inverters waveforms in term of the voltage or current of the waveforms issmooth and without distortion. The artificial neural network (ANN) technique toobtaining proper switching angles sequences for a uniform step asymmetrical modifiedmultilevel inverter by eliminating specified higher-order harmonics while maintainingthe required fundamental voltage and current waveform. However, through this paper amodified CHB-MLI are proposed using artificial intelligence optimization techniquebased on modulation Selective Harmonic Elimination (SHE-PWM). A most powerfulmodulation technique that used to minimize a harmonic contants during the outoutwaveform of multilevel inverter is a SHE-PWM method. The proposed a five-levelModified Cascaded H-Bridge Multilevel Inverter (M-CHBMI) with ANN controller toimprove the output voltage and current performance and achieve a lower TotalHarmonic Distortio...
DESIGN AND IMPLEMENTATION OF A FUZZY LOGIC CONTROLLER FOR MULTILEVEL INVERTER TOPOLOGY.
IJRCAR, 2013
It has been found that by using Fuzzy Logic Control scheme can greatly reduce harmonics distortions generated by the Multilevel Inverter. Harmonics reduction is the main consideration in the inverter circuit. The performance of the multilevel inverter increased by the reduction of THD. Multilevel inverters widely accepted for high-power high-voltage applications. In this research work, a new topology with a reversing-voltage component is proposed to improve the multilevel performance. This topology requires fewer components compared to existing inverters (particularly in higher levels) and requires fewer carrier signals and gate drives. The output voltage is regulated at a desired level in the face of source voltage disturbances or load disturbances using fuzzy logic control scheme. Both PI control scheme and fuzzy logic control scheme are analysed by using Matlab simulation. The inverter is proposed to deliver 40V / 300W. The source voltage variation can be anywhere between 24 volts and 50 volts DC. A prototype of the seven-level proposed topology is built and tested to show the performance of the inverter by experimental results. The percentage THD values of the multilevel inverter was analysed by using PI control scheme and Fuzzy Logic Control scheme. In this research work the current harmonics distortion was reduced by using Fuzzy Logic Control scheme, there was reduction of current THD 2.49 % , which increases the performance of the multilevel inverter.
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International Journal of Electrical Power & Energy Systems, 2014
This paper demonstrates an Artificial Intelligence (AI) based controller for 5-level, cascade H-bridge inverter for harmonic compensation and dc voltage regulation under different loading conditions for high voltage applications. In the proposed topology, the artificial neural network (ANN) is applied for obtaining compensating current and two Fuzzy Logic Controllers (FLC) are designed for dc voltage regulation and current error adjustment. The fuzzy logic controlled current error is then used for multicarrier Phase Shifted Pulse Width Modulation (PSPWM) for generating gate pulses for the inverter. The 5-level, Cascade H-bridge Multilevel Inverter (CHBMLI) is used as active harmonic filter. The ANN based instantaneous power theory is applied for reference current estimation. Simulation results are obtained in MATLAB/ SIMULINK for diode bridge rectifier with RL/RC as nonlinear loads, using simpower system and fuzzy tool box. The proposed topology performance is justified through exhaustive simulation under various loading conditions. The total harmonic distortion in source current (THD i ) is being used as evaluation criteria to quantify the results. The THD i obtained by applying PI and AI based controller are compared and are well within the IEEE 519, 1992 std. limits. The proposed method is verified through experimentation by developing prototype with dSPACE 1103 interface.
Indonesian Journal of Electrical Engineering and Computer Science, 2020
This paper confers an investigation of a Selective Harmonic Elimination (SHE) technique has gained wide acceptance for many AC drive applications, due to a higher DC bus voltage utilization (higher output voltage compared with the Sinusoidal Pulse Width Modulation (SPWM), lower harmonic distortions and easy digital realization.” In recent years, the SHE technique was extensively adopted in multilevel inverters since it offers greater numbers of switching for obtaining further improvements of AC drive performances. “Nevertheless, the use of SHE-associated multilevel inverters will optimize the switching angles based on Artificial Neural Networks (ANN) compared with Particle Swarm Optimization (PSO) to reduce the Total Harmonic Distortion (THD) of the modified CHB-MLI output voltage within permissible limits. The main objectives of this paper are the design and testing of the CHB-MLI modified topology laboratory for a nine-level single-phase prototype.” Also demonstrated were the expe...
Application of ANN to the Control by Elimination Harmonics of a Seven Level Voltage Inverter
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This study, deals with the artificial neural networks (ANN) implementation problem of the PWM harmonics elimination strategy applied to the control of a seven levels voltage inverter. The implementation of this method requires initially, calculating the switching angles related to power components. Their determination is carried out in order to cancel the harmonics 5, 7 and 11 and to control the fundamental voltage output. The computation of the switching angles is carried out for a large range of the variations of the modulation index. In order to avoid dealing with the tabulation method which requires an important size of storage memory for the computed values, it is proposed to generate these angles using an ANN. Thus, after the training phase, the elaborate ANN is able to reproduce the switching angles related to the modulation index for the control of a seven levels voltage inverter. So, for a real time control, it is sufficient to implement this network embedding the obtained synaptic weights.
ANFIS control of a shunt active filter based with a five-level NPC inverter to improve power quality
International Journal of Electrical and Computer Engineering (IJECE), 2021
This paper addresses the problem of power quality, and the degradation of the current waveform in the distribution network which results directly from the proliferation of the nonlinear loads. We propose to use a five-level neutral point clamped (NPC) inverter topology for the implementation of the shunt active filter (SAPF). The aim of the SAPF is to inject harmonic currents in phase opposition at the connection point. The identification of harmonics is based on the pq method. A neuro-fuzzy controller based on ANFIS (adaptive neuro fuzzy inference system) is designed for the SAPF. The simulation study is carried out using MATLAB/Simulink and the results show a significant improvement in the quality of energy and a reduction in total harmonic distortion (THD) in accordance with IEC standard, IEEE-519, IEC 61000, EN 50160.
IRJET, 2022
This paper presents a comparative study of seven-level and eleven-level Cascaded H-Bridge (CHB) inverter in power system for harmonic compensation. Integrating the photovoltaic (PV) system and grid requires power electronic converters. Inverters convert DC electricity produced by the PV system into AC electricity for loads. Multilevel inverters (MLI) replaces conventional inverters and are widely implemented in high-voltage and high-power applications due to the improved conversion efficiency, reduced stress on the switches etc... Total Harmonic Distortion (THD) is the most important power quality issue in multilevel inverters and can be reduced by SPWM technique and further reduced by using a controller that can able to withstand the static and dynamic conditions. A rule-based fuzzy logic controller design is described and produces better harmonic reduction than a PI controller. A grid connected inverter model using SPWM technique with PI controller and fuzzy logic controller will be implemented in MATLAB and the harmonic distortion analysis is evaluated at different states.
Optimum control of multilevel inverters using Artificial Neural Networks
2008
Estimation of optimum switching angles for multilevel converters so as to produce the required fundamental voltage while at the same time eliminate specified lower order harmonics through Artificial Neural Networks (ANNs) is presented. The proposed technique uses the best performance solutions (lowest THD solutions) as the training data set for proposed ANN system. This technique can be applied to multilevel inverters with any number of levels. As an example, in this paper estimation results of optimum switching angles are given for seven levels inverter to eliminate the 5th and 7th harmonics. After training the proposed ANN system, a large and memory-demanding look-up table replaced with trained neural network to generate the optimum switching angles with lowest THD for a given modulation index. The simulation results are presented in PSCAD/EMTDC software package to validate the accuracy of estimation results by proposed ANN system.